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检索条件"机构=Biomedical Data Science and Machine Learning Group"
286 条 记 录,以下是111-120 订阅
排序:
GSCLIP: A Framework for Explaining Distribution Shifts in Natural Language
arXiv
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arXiv 2022年
作者: Zhu, Zhiying Liang, Weixin Zou, James Department of Machine Learning Carnegie Mellon University PA United States Department of Computer Science Stanford University CA United States Department of Biomedical Data Science Stanford University CA United States Chan Zuckerberg Biohub San FranciscoCA United States
Helping end users comprehend the abstract distribution shifts can greatly facilitate AI deployment. Motivated by this, we propose a novel task, dataset explanation. Given two image data sets, dataset explanation aims ... 详细信息
来源: 评论
Pattern Discovery in an EEG database of Depression Patients: Preliminary Results
Pattern Discovery in an EEG Database of Depression Patients:...
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International Conference on Measurement
作者: Kateřina Hlaváčková-Schindler Christina Pacher Claudia Plant Mykola Lazarenko Milan Paluš Jaroslav Hlinka Aditi Kathpalia Martin Brunovský Data Mining and Machine Learning Research Group Faculty of Computer Science University of Vienna Vienna Austria Department of Complex Systems Institute of Computer Science Czech Academy of Sciences Prague Czechia Clinical Research Programme National Institute of Mental Health Klecany Czechia
The ability to predict response to medication treatment of depressed patients, either early in the course of therapy or before treatment even begins can avoid trials of ineffective therapy and save patients from prolo...
来源: 评论
Computationally Efficient Approximations for Matrix-based Rényi's Entropy
arXiv
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arXiv 2021年
作者: Gong, Tieliang Dong, Yuxin Yu, Shujian Dong, Bo The School of Computer Science and Technology Xi'an Jiaotong University Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi’an710049 China The Machine Learning Group UiT - The Arctic University of Norway Department of Computer Science Vrije University Amsterdam Amsterdam Netherlands
The recently developed matrix-based Rényi's αorder entropy enables measurement of information in data simply using the eigenspectrum of symmetric positive semi-definite (PSD) matrices in reproducing kernel H... 详细信息
来源: 评论
Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
arXiv
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arXiv 2024年
作者: Dietrich, Konstantin Prager, Raphael Patrick Doerr, Carola Trautmann, Heike Big Data Analytics in Transportation TU Dresden Germany ScaDS.AI Dresden Germany Data Science: Statistics and Optimization University of Münster Germany Sorbonne Université CNRS LIP6 Paris France Machine Learning and Optimisation Paderborn University Germany Data Management and Biometrics Group University of Twente Netherlands
Exploratory landscape analysis (ELA) is a well-established tool to characterize optimization problems via numerical features. ELA is used for problem comprehension, algorithm design, and applications such as automated... 详细信息
来源: 评论
EXPRESSIVITY AND SPEECH SYNTHESIS
arXiv
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arXiv 2024年
作者: Triantafyllopoulos, Andreas Schuller, Björn W. Technical University of Munich MRI Munich Germany GLAM – Group on Language Audio & Music Imperial College London United Kingdom MCML – Munich Center for Machine Learning Munich Germany MDSI – Munich Data Science Institute Munich Germany
Imbuing machines with the ability to talk has been a longtime pursuit of artificial intelligence (AI) research. From the very beginning, the community has not only aimed to synthesise high-fidelity speech that accurat... 详细信息
来源: 评论
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation
arXiv
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arXiv 2023年
作者: Bender, Sidney Anders, Christopher J. Chormai, Pattarawat Marxfeld, Heike Herrmann, Jan Montavon, Grégoire Machine Learning Group Technische Universität Berlin Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin Germany Max Planck School of Cognition Leipzig Germany BASF SE Ludwigshafen am Rhein Germany Department of Mathematics and Computer Science Freie Universität Berlin Germany
This paper introduces a novel technique called counterfactual knowledge distillation (CFKD) to detect and remove reliance on confounders in deep learning models with the help of human expert feedback. Confounders are ... 详细信息
来源: 评论
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation
Towards Fixing Clever-Hans Predictors with Counterfactual Kn...
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International Conference on Computer Vision Workshops (ICCV Workshops)
作者: Sidney Bender Christopher J. Anders Pattarawat Chormai Heike Marxfeld Jan Herrmann Grégoire Montavon Machine Learning Group Technische Universität Berlin Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin Germany Max Planck School of Cognition Leipzig Germany BASF SE Ludwigshafen am Rhein Germany Department of Mathematics and Computer Science Freie Universität Berlin Germany
This paper introduces a novel technique called counterfactual knowledge distillation (CFKD) to detect and remove reliance on confounders in deep learning models with the help of human expert feedback. Confounders are ...
来源: 评论
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain
arXiv
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arXiv 2021年
作者: Harder, Paula Pfreundt, Franz-Josef Keuper, Margret Keuper, Janis Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany Scientic Computing University of Kaiserslautern Kaiserlautern Germany Fraunhofer Center Machine Learning Germany Data and Web Science Group University of Mannheim Germany Offenburg University Germany
—Despite the success of convolutional neural networks (CNNs) in many computer vision and image analysis tasks, they remain vulnerable against so-called adversarial attacks: Small, crafted perturbations in the input i... 详细信息
来源: 评论
Analyzing the Structure of Attention in a Transformer Language Model
arXiv
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arXiv 2019年
作者: Vig, Jesse Belinkov, Yonatan Palo Alto Research Center Machine Learning and Data Science Group Interaction and Analytics Lab Palo AltoCA United States Harvard John A. Paulson School of Engineering and Applied Sciences MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States
The Transformer is a fully attention-based alternative to recurrent networks that has achieved state-of-the-art results across a range of NLP tasks. In this paper, we analyze the structure of attention in a Transforme... 详细信息
来源: 评论
Myocarditis Diagnosis: A Method using Mutual learning-Based ABC and Reinforcement learning
Myocarditis Diagnosis: A Method using Mutual Learning-Based ...
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International Symposium on Computational Intelligence and Informatics
作者: Saba Danaei Arsam Bostani Seyed Vahid Moravvej Fardin Mohammadi Roohallah Alizadehsani Afshin Shoeibi Hamid Alinejad-Rokny Saeid Nahavandi Adiban Institute of Higher Education Semnan Iran Department of mechanical engineering of biosystems Urmia university Department of exercise physiology & health science University of tehran Internship in UNSW BioMedical Machine Learning Lab Sydney NSW Australia Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Waurn Ponds Victoria Australia UNSW Data Science Hub The University of New South Wales (UNSW Sydney) Sydney New South Wales Australia BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney Sydney NSW Australia
Myocarditis occurs when the heart muscle becomes inflamed and inflammation occurs when your body’s immune system responds to infections. It can be diagnosed using cardiac magnetic resonance image (MRI), a non-invasiv... 详细信息
来源: 评论